vbatts/llama.cpp
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

convert*.py: inline source uuid generation approach

Browse source
This commit is contained in:
brian khuu 2024-07-27 13:03:13 +10:00
parent 0c491520a8
commit 3fb690e91b
2 changed files with 16 additions and 35 deletions
Download patch file Download diff file Expand all files Collapse all files

36
convert_hf_to_gguf.py
View file

@ -64,6 +64,7 @@ class Model:
gguf_writer: gguf.GGUFWriter
model_name: str | None
metadata_override: Path | None
generated_source_uuid: str | None
# subclasses should define this!
model_arch: gguf.MODEL_ARCH
@ -257,23 +258,18 @@ class Model:
return False
def generate_source_tensors_uuid(self) -> str:
def prepare_tensors(self):
uuidv5_sha1 = hashlib.sha1()
uuidv5_sha1.update(uuid.UUID('ef001206-dadc-5f6d-a15f-3359e577d4e5').bytes)
for name, data_torch in self.get_tensors():
# we don't need these
if name.endswith((".attention.masked_bias", ".attention.bias", ".rotary_emb.inv_freq")):
continue
data: np.ndarray = data_torch.to(torch.float64).squeeze().numpy()
uuidv5_sha1.update(data.tobytes('C'))
return str(uuid.UUID(bytes=uuidv5_sha1.digest()[:16], version=5))
def prepare_tensors(self):
max_name_len = max(len(s) for _, s in self.tensor_map.mapping.values()) + len(".weight,")
for name, data_torch in self.get_tensors():
uuidv5_data_buffer: np.ndarray = data_torch.to(torch.float64).numpy()
uuidv5_sha1.update(uuidv5_data_buffer.tobytes('C'))
# we don't need these
if name.endswith((".attention.masked_bias", ".attention.bias", ".rotary_emb.inv_freq")):
continue
@ -353,6 +349,9 @@ class Model:
self.gguf_writer.add_tensor(new_name, data, raw_dtype=data_qtype)
# Upon missing source model uuid, generate uuid based on source tensor content
self.generated_source_uuid = str(uuid.UUID(bytes=uuidv5_sha1.digest()[:16], version=5))
def set_type(self):
self.gguf_writer.add_type(gguf.GGUFType.MODEL)
@ -396,15 +395,12 @@ class Model:
# output in the same directory as the model by default
self.fname_out = self.dir_model / f"{fname_default}.gguf"
# Upon missing source model uuid, generate uuid based on source tensor content
if not vocab_only and self.metadata.source_uuid is None:
self.metadata.source_uuid = self.generate_source_tensors_uuid()
logger.info(f"generating general.source_uuid: {self.metadata.source_uuid}")
# Upon missing model uuid, generate uuid based on tensor content
if not vocab_only and self.metadata.uuid is None:
self.metadata.uuid = self.gguf_writer.generate_tensors_uuid()
logger.info(f"generating general.uuid: {self.metadata.uuid}")
if not vocab_only:
if self.metadata.source_uuid is not None:
logger.info(f"Source UUID present: {self.metadata.source_uuid}")
elif self.generated_source_uuid is not None:
logger.info(f"Source UUID missing. Using generated source uuid: {self.generated_source_uuid}")
self.metadata.source_uuid = self.generated_source_uuid
self.set_type()

15
gguf-py/gguf/gguf_writer.py
View file

@ -2,8 +2,6 @@ from __future__ import annotations
import logging
import os
import uuid
import hashlib
import shutil
import struct
import tempfile
@ -419,19 +417,6 @@ class GGUFWriter:
self.state = WriterState.WEIGHTS
def generate_tensors_uuid(self) -> str:
uuidv5_sha1 = hashlib.sha1()
uuidv5_sha1.update(uuid.UUID('ef001206-dadc-5f6d-a15f-3359e577d4e5').bytes)
for tensors in self.tensors:
# relying on the fact that Python dicts preserve insertion order (since 3.7)
for name, ti in tensors.items():
assert ti.tensor is not None
assert ti.tensor.nbytes == ti.nbytes
uuidv5_sha1.update(ti.tensor.tobytes('C'))
return str(uuid.UUID(bytes=uuidv5_sha1.digest()[:16], version=5))
def write_tensors_to_file(self, *, progress: bool = False) -> None:
self.write_ti_data_to_file()